In the field of industrial manufacturing and quality control, machine vision systems have always been an important tool to improve work efficiency and ensure product quality. With the development of technology, the difference between traditional visual inspection systems and modern machine vision technology has become more and more significant. This article The unique characteristics of these two technologies will be explored, and their advantages, disadvantages, and applicable scenarios will be compared.
Table of Contents
- 1. Traditional visual inspection technology
- 2. Modern machine vision technology
- 3. Comparison of application scenarios
- 4. Recommended machine vision industrial computers
1. Traditional visual inspection technology
Traditional visual inspection technology mainly relies on basic image capture devices and simple image processing algorithms. Such systems usually use cameras to capture product images, and then use software to compare images in a database to identify defects or discrepancies.
The main advantage is that the implementation cost is low and it is sufficient for some basic quality inspection scenarios. However, its disadvantages are also obvious, including sensitivity to environmental conditions, slow inspection speed, limited accuracy, and difficulty in handling complex or irregularly shaped objects.
2. Modern machine vision technology
In contrast, modern machine vision technology integrates more advanced image perception hardware and complex image processing algorithms, such as artificial intelligence and deep learning, which can automatically identify various defects and accurately classify, locate and track objects even in complex backgrounds.
The advantages of modern machine vision systems are their excellent detection speed, high accuracy and ability to handle complex applications; in addition, they can work under different lighting and environmental conditions, providing more flexible applications. However, these systems are expensive to deploy and maintain and require more technical support.
3. Comparison of application scenarios
In terms of application scenarios, traditional visual inspection technology is still applicable in some simple and low-speed production lines due to its cost-effectiveness, such as those manufacturing processes with simple product shapes and low inspection requirements.
But modern machine vision technology is more suitable for high-speed and highly automated production lines, especially those that require high-precision inspection or operate in a changing environment, such as assembly and quality inspection of electronic components, and identification and assembly of parts in automobile manufacturing.
4. Recommended machine vision industrial computers
Product model: SIN-610L-JH420MA
This product uses Intel H420E chipset, supports Core 10th generation processors, and can be equipped with NVIDIA high-performance graphics cards to ensure fast processing and high accuracy of image data.
It supports a variety of industrial cameras and sensors, can be easily integrated into different machine vision systems, and has strong scalability, supports a variety of communication protocols and interfaces, such as 6 COM ports, 9 USB ports, etc., and has 2 PCIe expansion slots and 5 PCI expansion slots, which are convenient for future upgrades and function expansions.
In summary, although traditional visual inspection technology is still used in some fields, modern industrial machine vision technology is more widely used. SINSMART high-performance industrial PC for machine vision supplier, with its excellent performance and flexibility, is the choice of many users. Welcome to inquire.
For those requiring a more robust solution, we also offer industrial PC 4U and 2U industrial PC, which are perfect for a wide range of applications. Additionally, custom rackmount PC options are available for those needing tailor-made configurations. As an experienced industrial computer manufacturer, we specialize in high-performance solutions like Advantech industrial PC to meet specific system requirements.
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